Wireless Sensor Networks for IoT

Traditional Network forms the core of any networking architectures and protocols which has been desgned and developed over time. All the modern developments in networking such as IoT networks, SDN networs, service-oriented networks, QoS and QoE aware networks etc are based on the core concepts, algorithms and protocols of traditional networks. Therefore the importance and significance of traditional networking is as relevant as before and demands equal attention. Any change in the existing traditional networking architectures will affect all other technologies as well. The various core concepts of traditional networks such as routing protocols, congestion control and avoidance, throughput, TCP/IP protocols among others are the base upon which all modern networking protocols are built upon

Among the various modern networks that are readily deployed today, Wireless Sensor Networks (WSNs) are of special interest. A subtype of broader IoT networks, WSNs consists of wireless interconnected networks of small low-power sensor devices that sense some environmental parameters at regular intervals of time and send them over to some central storage or database. The central storage or database can also be fog or cloud across the Internet. WSN protocols to maximize the performance of the sensor nodes, minimize the latency of communication and reduce the consumption of power is an active area of research today

Here we study the various works and research on traditional and core netwroking concepts as well as wireless sensor networks. These will help us to understand the problems that still remains in the above domains as well as their solutions and identify new ideas and avenues for further research.

 

Wireless Sensor Networks in the Presence of Dumb nodes


A sensor node is termed as “dumb” when it can sense its surroundings, but cannot communicate with its neighbors due to shrinkage in communication range attributed to adverse environmental effects such as rainfall, fog, and high temperature etc.

In this work, a scheme named CoRAD is proposed for the re-establishment of lost connectivity using adjustable communication range sensor nodes in the presence of dumb nodes in stationary wireless sensor networks (WSNs). The mere activation of intermediate sleep nodes cannot guarantee re-establishment of connectivity, because there may not exist neighbor nodes of the isolated nodes. On the contrary, the increase in the communication range of a single sensor node may make it die quickly. Hence, a price-based scheme is proposed that helps the network to self-organize and re-connects the isolated nodes by activating some intermediate sleep nodes increasing the communication range of nodes. The scheme also deactivates the additionally activated nodes and reduces the increased communication range, when the dumb nodes resume their normal behavior on the return of favorable environmental conditions.

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In this work, we propose a mechanism to detect dumb nodes in a Wireless Sensor Network. The detection of dumb nodes is essential to re-establish network connectivity. However, the temporal behavior of a dumb node in a network makes the detection of such a node challenging. In the present work, we address a plausible solution to this problem by taking into account the evidence from neighboring nodes. Here we use GPS-enabled sensor nodes deployed over terrain and periodic 'HELLO' messages among the sensor nodes for dumb node detection. The 'HELLO' messages have a specific format and each of the nodes assigns a reward on receiving 'HELLO' messages from neighboring nodes. Dumb nodes in the WSN are thus detected.

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In this work, we propose D3, a distributed approach for the detection of dumb nodes in Wireless Sensor Networks. The presence of dumb nodes makes the network unable to provide the required services. In this proposed scheme, we use the Cumulative Sum (CUSUM) test, which helps in detecting the dumb behavior. The simulation results show that there is 56% degradation in detection percentage with the increment in the detection threshold whereas energy consumption and the message overhead increases by 40% with the increment in the detection threshold. The detection problem is further analyzed using the Markov chain and the proposed solution has been theoretically characterized. We have also introduced the concept of aperiodic 'HELLO' messages considering the energy-constrained nature of WSNs.

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In this work, we study the effects of dumb nodes on Wireless Sensor Networks. We consider the effects of dumb nodes on the, otherwise, energy-efficient stationary WSNs having complete network coverage achieved using a sufficient number of activated sensor nodes. While the presence of redundancy in the deployment of nodes, or the number of active nodes can guarantee communication opportunities, such deployment is not necessarily energy-efficient and cost-effective. The dumb behavior of nodes results in wastage of power, thereby reducing the lifetime of a network. Such effects can be detrimental to the performance of WSN applications. We perform simulation studies which indicate that the existence of dumb nodes degrades the performance of the network. Therefore, it is imperative to identify and explore the different effects of a dumb node in WSNs.

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In this work, a scheme called LECRAD is proposed for the re-construction of temporarily lost connectivity in the presence of dumb nodes in stationary wireless sensor networks. The dumb behavior of a node leads to network partitioning and node isolation, which results in disruption of connected topology. The proposed scheme in this paper reconstructs the lost connectivities between nodes by activating intermediate sleep nodes or by adjusting the communication range of the sensor nodes, while there is no neighbor node within the reduced communication range. A learning automata-based approach is used for the activation of intermediate sleep nodes or adjustment of communication range of isolated or intermediate nodes to decrease the message overhead and energy consumption of the network. We perform simulation which shows that the proposed scheme exhibits better energy efficiency and message overhead.

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In this work, the problem of topology control for self-adaptation in stationary Wireless Sensor Networks (WSNs) is revisited, specifically for the case of networks with a subset of nodes having temporary connection impairment between them. This study focuses on misbehaviors arising due to the presence of “dumb” nodes is a WSN environment. Activation of all the sensor nodes simultaneously is not necessarily energy-efficient and cost-effective. To maintain self-adaptivity of the network, two algorithms named Connectivity Re-establishment in the presence of Dumb nodes (CoRD) and Connectivity Re-establishment in the presence of Dumb nodes Without Applying Constraints (CoRDWAC) are designed. The performance of these algorithms is evaluated through simulation-based experiments. It has been observed that the performance of CoRD is better than the existing topology control protocols.

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Wireless Sensor Networks Applications in Agricultural IoT

Application of Wireless Sensor Networks span across various fields and agriculture is one of them. In this work, we propose a hardware prototype using Wireless Sensor Network (WSN) for intruder detection in an agricultural field. The proposed system is named Agricultural Intrusion Detection (AID). It helps to generate alarms in the farmer’s house and at the same time transmits a text message to the farmer’s cell phone when an intruder enters into the field. To implement the proposed scheme, we design and deploy Advanced Virtual RISC (AVR) microcontroller-based wireless sensor boards over an outdoor environment and evaluate the performance. The architecture of AID is divided into layers with each layer having its functionalities. The nodes are deployed on an agricultural field and their performance studied and accurately measured. In each of the cases, we observe that accuracy is always above 95%.

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Topology Management in IoT Networks

In this paper, the problem of ensuring packet delivery ratio and high network lifetime in wireless sensor networks (WSNs) in the presence of single or multiple jammers is studied using Single-Leader-Multiple-Followers Stackelberg game theory. Here, a topology control scheme is proposed, in which the sink node, which acts as the leader, identifies the set of jamming affected nodes while sensor nodes which act as followers need to decide on optimum transmission power level. A scheme, named TC-JAM, for ensuring packet delivery ratio, while avoiding jammers and increasing network lifetime in WSNs has been developed. In TC-JAM, the sensor nodes have simple hardware with a single interface for communication, i.e., the sensor nodes have a single channel for communication. Additionally, each sensor node has a provision to vary its transmission power according to the chosen strategies. Using TC-JAM, the energy consumption of the overall network reduces by up to 62%, and the network lifetime increases by 56-73%.

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In this paper, we propose a distributed topology management algorithm, named T-Must, which orchestrates a coalition formation game between the camera and scalar sensor nodes, for use in wireless multimedia sensor networks. In the proposed solution, connectivity among the peer camera sensor nodes is maintained and coverage is ensured between them. As it is very evident for proper monitoring, multimedia data like video streams are essential. In the case of camera sensor nodes, power consumption and the price of the nodes are important. Therefore to increase the network lifetime, topology is controlled by forming a coalition between the camera and scalar sensor nodes. Upon the occurrence of an event, the scalar sensor nodes send scalar data to their associated camera sensor nodes. If the scalar data received from scalar sensor nodes cross a pre-configured threshold, the associated camera sensor node in the coalition starts sensing the event, captures the video data, and forwards the video data towards other coalitions or sink.

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Energy Efficient IoT Networks

In this paper, we present the design of a new sensor node, named Multipurpose EnerGy-efficient Adaptable low-cost sensor Node (MEGAN), with all the desired features such as reconfigurability, flexibility, energy-efficiency, and low-cost required to build the Internet of Things (IoT). Apart from the ability to interface a maximum of 32 different sensors and actuators, MEGAN allows a user to choose the desired communication module, depending on the required range of communication. A novel power management circuit to extend the lifetime of the resource-constrained sensor node and it has an integrated circuit onboard that can use the energy harvested from any unregulated energy source. MEGAN combats a major drawback of application-specific sensor nodes, because of the integration of switches and a programming port. The flexibility of MEGAN, for the integration of any sensor or actuator, makes it a multipurpose adaptable sensor node. Analysis has shown the energy efficiency and superiority of the hardware design.

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